Abstract

Background: African American (AA) women were until recently less likely to be diagnosed with breast cancer (BC) and remain more likely to die from the disease when compared to non-Latina (nL) White (White) counterparts. High mammographic breast density (HBD) is a well-established risk factor for developing BC, but there is no consensus in the literature regarding whether HBD varies by race/ethnicity (R/E). AA women have been reported to have lower breast density compared to nL Whites, Latinas and Asians in some but not all studies. Only a handful of studies have examined factors (e.g. BMI, age, parity, hormone therapy, menarche and menopause) that might account for racial/ethnic differences in HBD. Therefore, we endeavored to examine racial/ethnic differences in HBD and the potential role of socioeconomic status (SES), obesity and parity in observed racial/ethnic differences in a large cohort of women undergoing screening mammography. Methods: We used data on 133,983 women aged 40-79 undergoing their most recent screening mammogram between 2001 and 2015 within a large healthcare organization and whose R/E was nL White, nL Black, Latina, Native American, or Asian/Pacific Islander (Asian). At the screening mammogram, each breast received a breast density score from the interpreting radiologist using the American College of Radiology Breast Imaging Reporting and Data System (BIRADS 1-4), defined as fatty (BIRADS 1), scattered fibroglandular (BIRADS 2), heterogeneously dense (BIRADS 3) or extremely dense (BIRADS 4). We defined breast density as the maximum value of the two breast density scores. We defined HBD as a breast density BIRADS score of 3 or 4 (versus 1 or 2). SES was defined by creating two census-tract level, aggregate variables for disadvantage and affluence. Body mass index (BMI) was defined from patient reported height and weight. Women also reported their number of live-births (parity) and menopausal status. HBD was modeled in logistic regression with model-based standardization (predictive margins) to estimate age-adjusted prevalence of HBD by R/E, before and after including patient factors in the model that might explain R/E differences in HBD. Results: Lower BMI, lower parity, and higher socioeconomic status were each associated with HBD in all analyses (p<0.0001), though the magnitude of the association for SES was greatly attenuated with adjustment for BMI. In models adjusted only for age, HBD was greatest for Asian women (66%), followed by nL White and Native American women (51% and 50%) and was lowest for nL Black and Latina women (46% and 45%). Upon adjusting for BMI, a very different pattern emerged whereby HBD was greatest for Asian and nL Black women (56% and 54%) and lowest for nL White and Latina women (48% and 47%). With additional adjustment for SES, obesity and parity, HBD remained greatest for Asian and nL Black women (55% and 55%) and lowest for nL White and Latina women (47% and 48%). Conclusions: Racial and ethnic differences in HBD appear to be the result most notably of racial/ethnic differences in BMI (a marker for obesity), and also of parity and socioeconomic status. Results suggest that if obesity, parity and socioeconomic status were equally distributed among racial and ethnic groups in our society, breast density would be greatest for Asian and nL Black women and lowest for nL White and Latina women. These findings would be in agreement with a few recent studies which reported nL Black women as more likely to have HBD after accounting for BMI and reproductive factors. The persistent association of SES with HBD after adjusting for BMI and parity may be the result of socioeconomic or environmental factors or may be due to residual effects of parity and BMI not accounted for in the model.